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. This work involves developing novel techniques, algorithms, and software packages that enable more robust and scalable approaches to cybersecurity using AI-based techniques. In addition to technical
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, molecular properties, and pathological images. Strong knowledge and experience in data science algorithms, methods, and analysis techniques. Experience in programming using Python and R languages and working
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approaches for important questions in neuroscience. We have multiple current and incoming NIH projects to establish cellular cell type architecture maps of mammalian brains using mice as an animal model. Three
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decision with multiple data sources. One example is to develop the semi-supervised methods and dynamic system interfacing algorithms to produce an automated and real-time information exchange across
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to work on projects in the modeling of representative democracy. The primary role of these Research Associates will be to anchor multiple research projects in electoral systems (such as ranked choice
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powerful model platform, the lab aims to develop an integrative understanding of how animals adaptively respond to their sensory world, from molecular detection to the neural algorithms of complex motor
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intelligence is preferred in candidates applying for this position. Responsibilities Design, develop, test, and debug complex software programs. Implement and optimize algorithms (ML + AI) for data-intensive
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multiple priorities and a multi-disciplinary environment. Qualifications: Minimum Bachelor’s Degree in Machine Learning, Data Science, or Statistics, or another field of science or engineering with relevant
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environments, taking into consideration new work arrangements (e.g., gig work and remote work) and technology (e.g., remote control, algorithmic management). The dominance of AT has contributed to an over
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”, led by Associate Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case